- Use SPSS and Framingham_One Sample data to compute and interpret 95% CI for the following variables:
- Number of cigarettes per day (CIGPDAY).
- Time to MI (TIMEMI)
- Blood Glucose level (GLUCOSE)
- Use SPSS and Framingham_Independent Sample data to compute and interpret 95% CI for the mean difference between those with diabetes (DIABETES = 1) and those without diabetes (DIABETES =0) for the following variables:
- Number of cigarettes per day (CIGPDAY).
- Time to MI (TIMEMI)
- Blood Glucose level (GLUCOSE)
- Use SPSS and Framingham_Paired Sample data to compute and interpret 95% CI for the mean difference between base line (_1) and second follow up period (_3) for the following variables:
- Body Mass Index (BMI)
- Total Cholesterol (TOTCHOL)
- Glucose level (GLUCOSE)
- Use SPSS and Framingham_RROR Sample data to compute and interpret 95% CI OR and RR between smokers (CURSMOKE = 1) and non-smokers (CURSMOKE = 2) for the following outcome variables:
- Diabetes (DIABETES)
- MI (PREVMI)
- CHD (PREVCHD)
- Use SPSS and Framingham_RROR Sample data to compute and interpret 95% CI OR and RR between users of BP medications (BPMEDS= 1) and non-users of BP medications (BPMEDS = 2) for the following outcome variables:
- CHD (PREVCHD)
- Stroke (PREVSSTRK)
- Diabetes (DIABETES)
Note for #4 and #5: (1=has the disease, 2=does not have the disease)